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                    MLSQL Stack
            
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                    K8s部署
            
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                    Yarn部署
            
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                    Analysis Workshop使用
            
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                    Admin管理后台之Engine配置
            
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                    使用窗口进行数据分析
            
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                    复杂组合条件过滤
            
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                    MySQL数据库配置
            
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                    Json字段展开
            
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                    用MLSQL为Analysis Workshop开发插件
            
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                    MLSQL语言控制台使用
            
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                    MLSQL语法手册
            
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                    Select语法
            
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                    Train/Run/Predict语法
            
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                    Register语法
            
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                    分支语句
            
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                    MLSQL语法解析接口
            
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                    MLSQL批处理编程
            
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                    MLSQL数仓/数据湖使用
            
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                    Hive加载和存储
            
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                    Delta加载和存储以及流式支持
            
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                    MySQL Binlog同步
            
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                    加载和存储多种数据源
            
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                    JDBC
            
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                    ElasticSearch
            
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                    Solr
            
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                    HBase
            
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                    MongoDB
            
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                    Parquet/Json/Text/Xml/Csv
            
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                    jsonStr/script/mlsqlAPI/mlsqlConf
            
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                    内置常见UDF
            
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                    http请求
            
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                    常见函数
            
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                    一些有用的内置ET
            
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                    计算复杂的父子关系
            
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                    改变表的分区数
            
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                    如何发送邮件
            
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                <a href="../process/estimator_transformer/mlsql-watcher.html">
            
                    
                    数据采集组件mlsql-watcher使用
            
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        <li class="chapter " data-level="5.3" data-path="../stream/">
            
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                    MLSQL流编程
            
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                    Kafka和MockStream
            
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        <li class="chapter " data-level="5.3.2" data-path="../stream/kakfa_tool.html">
            
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                    MLSQL Kafka小工具集锦
            
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        <li class="chapter " data-level="5.3.3" data-path="../stream/data_convert.html">
            
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                    自动将Kafka中的JSON数据展开为表
            
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                    如何高效的AdHoc查询Kafka
            
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                    如何设置流式计算回调
            
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                    如何对流的结果以批的形式保存
            
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                    window/watermark的使用
            
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        <li class="chapter " data-level="5.3.8" data-path="../stream/stream_mysql_update.html">
            
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                    如何使用MLSQL流式更新MySQL数据
            
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        <li class="chapter " data-level="5.3.9" data-path="../stream/web_console.html">
            
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                    流结果输出到WebConsole
            
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        <li class="chapter " data-level="5.4" data-path="../ml/">
            
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                    MLSQL机器学习编程
            
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                    特征工程
            
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        <li class="chapter " data-level="5.4.1.1" data-path="../feature/nlp.html">
            
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                    文本向量化
            
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                    TFIDF
            
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        <li class="chapter " data-level="5.4.1.1.2" data-path="../feature/word2vec.html">
            
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                    Word2Vec
            
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        <li class="chapter " data-level="5.4.1.2" data-path="../feature/scale.html">
            
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                    特征平滑
            
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        <li class="chapter " data-level="5.4.1.3" data-path="../feature/normalize.html">
            
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                    归一化
            
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        <li class="chapter " data-level="5.4.1.4" data-path="../feature/confusion_matrix.html">
            
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                    混淆矩阵
            
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        <li class="chapter " data-level="5.4.1.5" data-path="../feature/some_extract.html">
            
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                    QQ/电话/邮件抽取
            
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        <li class="chapter " data-level="5.4.1.6" data-path="../feature/discretizer/">
            
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                    离散化
            
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                    Bucketizer
            
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        <li class="chapter " data-level="5.4.1.6.2" data-path="../feature/discretizer/quantile.html">
            
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                    Quantile
            
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                    Map转化为向量
            
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        <li class="chapter " data-level="5.4.1.8" data-path="../feature/rate_sample.html">
            
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                    数据集切分
            
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                    MLSQL Python支持
            
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                    环境依赖
            
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                    数据处理
            
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                    结合Python读取Excel
            
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                    结合Python保存Excel
            
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                    K8s下的Python资源限制
            
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                    dataMode 详解
            
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                    Python并行度你所需要知道的
            
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                    MLSQL内置算法
            
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                    ALS
            
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                    RandomForest
            
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                    LDA
            
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                    XGBoost
            
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                    部署算法API服务
            
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                    设计和原理
            
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                    部署流程
            
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                    MLSQL动态创建UDF/UDAF
            
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                    Python UDF
            
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                    Scala UDF
            
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                    Scala UDAF
            
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                    MLSQL Engine插件
            
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                    API on（Console/Engine）介绍
            
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                    MLSQL Console API指南
            
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                    脚本执行代理接口
            
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                    MLSQL Engine Liveness探针
            
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<p>&#x6709;&#x4E86;&#x8FD9;&#x4E9B;&#x6587;&#x4EF6;&#xFF0C;Spark&#x624D;&#x77E5;&#x9053;&#x5982;&#x4F55;&#x8FDE;&#x63A5;Hadoop&#x96C6;&#x7FA4;&#x3002;</p>
<p>&#x63A5;&#x7740;&#xFF0C;&#x5C31;&#x53EF;&#x4EE5;&#x53C2;&#x8003;<a href="http://docs.mlsql.tech/mlsql-console/howtouse/engine/" target="_blank">&#x5B89;&#x88C5;&#x90E8;&#x7F72;&#x6587;&#x6863;</a>&#x53BB;&#x90E8;&#x7F72;&#x4E86;&#x3002;</p>
<h2 id="&#x53EF;&#x80FD;&#x5B58;&#x5728;&#x7684;&#x95EE;&#x9898;"><a name="&#x53EF;&#x80FD;&#x5B58;&#x5728;&#x7684;&#x95EE;&#x9898;" class="anchor-navigation-ex-anchor" href="#&#x53EF;&#x80FD;&#x5B58;&#x5728;&#x7684;&#x95EE;&#x9898;"><i class="fa fa-link" aria-hidden="true"></i></a>&#x53EF;&#x80FD;&#x5B58;&#x5728;&#x7684;&#x95EE;&#x9898;</h2>
<p>CDH/HDP &#x6839;&#x636E;&#x7248;&#x672C;&#x4E0D;&#x540C;&#xFF0C;&#x4F1A;&#x5728;Yarn&#x8282;&#x70B9;&#x4E0A;&#x9ED8;&#x9ED8;&#x7684;&#x5E26;&#x4E0A;&#x4E00;&#x4E9B;&#x9ED8;&#x8BA4;Jar&#x5305;&#xFF0C;<strong>&#x53EF;&#x80FD;</strong>&#x4F1A;&#x53D1;&#x751F;Jar&#x5305;&#x51B2;&#x7A81;&#x3002;
&#x5BF9;&#x4E8E;HDP&#x5927;&#x5BB6;&#x53EF;&#x4EE5;&#x53C2;&#x8003;&#x8FD9;&#x7BC7;&#x6587;&#x7AE0;<a href="http://docs.mlsql.tech/zh/develop/ambari_multi_spark.html" target="_blank">Ambari hdp Spark&#x591A;&#x7248;&#x672C;&#x517C;&#x5BB9;</a>&#x83B7;&#x5F97;&#x4E00;&#x4E9B;&#x601D;&#x8DEF;.</p>
<p>&#x5BF9;&#x4E8E;Spark&#x8FD0;&#x884C;&#x5728;&#x5982; CDH,&#x6BD4;&#x5982;&#x6BD4;&#x8F83;&#x65E9;&#x7684;&#x7248;&#x672C;&#x5982;5.13.1&#xFF0C;&#x53EF;&#x80FD;&#x9700;&#x8981;&#x89E3;&#x51B3;&#x4E00;&#x4E9B;&#x95EE;&#x9898;&#xFF0C;&#x5927;&#x5BB6;&#x53EF;&#x4EE5;&#x6839;&#x636E;&#x5B9E;&#x9645;&#x7684;&#x9519;&#x8BEF;&#x6309;&#x56FE;&#x7D22;&#x9AA5;&#xFF1A;</p>
<h3 id="hdfs-kerberos-token&#x8FC7;&#x671F;&#x95EE;&#x9898;"><a name="hdfs-kerberos-token&#x8FC7;&#x671F;&#x95EE;&#x9898;" class="anchor-navigation-ex-anchor" href="#hdfs-kerberos-token&#x8FC7;&#x671F;&#x95EE;&#x9898;"><i class="fa fa-link" aria-hidden="true"></i></a>HDFS Kerberos token&#x8FC7;&#x671F;&#x95EE;&#x9898;</h3>
<p>&#x9519;&#x8BEF;&#x4FE1;&#x606F;&#x5927;&#x6982;&#x662F;&#x8FD9;&#x6837;&#xFF1A;</p>
<pre><code>spark hadoop.security.token.SecretManager token can&apos;t be found in cache
</code></pre><p>&#x539F;&#x56E0;&#x662F;&#x6253;&#x5305;&#x4F7F;&#x7528;hadoop&#x2013;2.7&#x5B98;&#x65B9;&#x662F;&#x6CA1;&#x6709;&#x89E3;&#x51B3;&#x8FD9;&#x65B9;&#x9762;&#x95EE;&#x9898;&#x7684;(&#x7EBF;&#x4E0A;&#x4E5F;&#x662F;&#x4F7F;&#x7528;cdh&#x7684;hadoop)</p>
<p>&#x89E3;&#x51B3;&#x65B9;&#x6CD5;&#xFF1A;&#x6253;&#x5305;&#x6307;&#x5B9A;cdh&#x7248;&#x672C;&#x7684;hadoop&#x4F9D;&#x8D56;&#xFF0C;&#x6307;&#x5B9A;-Dhadoop.version=2.6.0-cdh5.13.1    </p>
<h3 id="hdfs-native-snappy-library-not-available&#x95EE;&#x9898;"><a name="hdfs-native-snappy-library-not-available&#x95EE;&#x9898;" class="anchor-navigation-ex-anchor" href="#hdfs-native-snappy-library-not-available&#x95EE;&#x9898;"><i class="fa fa-link" aria-hidden="true"></i></a>HDFS native snappy library not available&#x95EE;&#x9898;</h3>
<p>&#x9519;&#x8BEF;&#x4FE1;&#x606F;&#x5927;&#x6982;&#x662F;&#x8FD9;&#x6837;&#xFF1A;</p>
<pre><code>native snappy library not available: this version of libhadoop was built without snappy support.
</code></pre><p>&#x89E3;&#x51B3;&#x65B9;&#x6CD5;&#xFF1A;&#x5728;SPARK_HOME/conf&#x4E0B;&#x7684;spark-env.sh &#x4E2D;</p>
<p>&#x6307;&#x5B9A;JAVA_LIBRARY_PATH&#x4E3A;native so&#x6587;&#x4EF6;&#x8DEF;&#x5F84;</p>
<pre><code class="lang-shell">export JAVA_LIBRARY_PATH=$JAVA_LIBRARY_PATH:\
/opt/cloudera/parcels/CDH/lib/hadoop/lib/native

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:\
/opt/cloudera/parcels/GPLEXTRAS/lib/hadoop/lib/native:\
/opt/cloudera/parcels/CDH/lib/hadoop/lib/native

export SPARK_DIST_CLASSPATH=/etc/hadoop/conf:\
/opt/cloudera/parcels/CDH/lib/hadoop/lib/*:\
/opt/cloudera/parcels/CDH/lib/hadoop/lib/native/*:\
/opt/cloudera/parcels/GPLEXTRAS/lib/hadoop/lib/*::
</code></pre>
<p>executor&#x7AEF;,&#x542F;&#x52A8;&#x811A;&#x672C;&#x6DFB;&#x52A0;java.library.path&#x4E3A;native so&#x6587;&#x4EF6;&#x8DEF;&#x5F84;</p>
<pre><code class="lang-shell">ENV SPARK_EXECUTOR_NATIVE_JAVA_OPTS=&quot;-Djava.library.path=/opt/cloudera/parcels/CDH/lib/hadoop/lib/native/&quot;

executor)
    shift 1
    CMD=(
      ${JAVA_HOME}/bin/java
      &quot;${SPARK_EXECUTOR_NATIVE_JAVA_OPTS[@]}&quot;
      &quot;${SPARK_EXECUTOR_JAVA_OPTS[@]}&quot;
      -Xms$SPARK_EXECUTOR_MEMORY
      -Xmx$SPARK_EXECUTOR_MEMORY
      -cp &quot;$SPARK_CLASSPATH:$SPARK_DIST_CLASSPATH&quot;
      org.apache.spark.executor.CoarseGrainedExecutorBackend
      --driver-url $SPARK_DRIVER_URL
      --executor-id $SPARK_EXECUTOR_ID
      --cores $SPARK_EXECUTOR_CORES
      --app-id $SPARK_APPLICATION_ID
      --hostname $SPARK_EXECUTOR_POD_IP
    )
    ;;
</code></pre>
<h3 id="https&#x8BBF;&#x95EE;&#x5F02;&#x5E38;"><a name="https&#x8BBF;&#x95EE;&#x5F02;&#x5E38;" class="anchor-navigation-ex-anchor" href="#https&#x8BBF;&#x95EE;&#x5F02;&#x5E38;"><i class="fa fa-link" aria-hidden="true"></i></a><a href="https://github.com/oracle/graal/issues/493" target="_blank">https&#x8BBF;&#x95EE;&#x5F02;&#x5E38;</a></h3>
<p>&#x9519;&#x8BEF;&#x4FE1;&#x606F;&#x5927;&#x6982;&#x662F;&#x8FD9;&#x6837;&#xFF1A;<code>PKIX path building failed: sun.security.provider.certpath.SunCertPathBuilderException</code>
&#x539F;&#x56E0;&#x662F;&#xFF1A;&#x8BBF;&#x95EE;https&#x670D;&#x52A1;&#x9700;&#x8981;&#x6307;&#x5B9A;&#x8BC1;&#x4E66;
&#x89E3;&#x51B3;&#x65B9;&#x6CD5;&#xFF1A;
&#x5C06;&#x5B89;&#x5168;&#x8BC1;&#x4E66;&#x5B89;&#x88C5;&#x540E;&#xFF0C; &#x6DFB;&#x52A0;&#x81F3;&#x672C;&#x5730;Jre  security&#x4E2D;&#xFF0C;</p>
<pre><code class="lang-shell">cd /Library/Java/JavaVirtualMachines/jdk1.8.0_131.jdk/Contents/Home/jre/lib/security &#x76EE;&#x5F55;&#x4E0B;&#x6267;&#x884C;:

keytool -import  -v -alias xxxxx -keystore
&quot;/Library/Java/JavaVirtualMachines/jdk1.8.0_131.jdk/Contents/Home/jre/lib/security/cacerts&quot;
-file &quot;/xxx/xxxx/xxxxx.cer&quot;
</code></pre>
<h3 id="spark3&#x548C;hadoop&#x517C;&#x5BB9;&#x95EE;&#x9898;"><a name="spark3&#x548C;hadoop&#x517C;&#x5BB9;&#x95EE;&#x9898;" class="anchor-navigation-ex-anchor" href="#spark3&#x548C;hadoop&#x517C;&#x5BB9;&#x95EE;&#x9898;"><i class="fa fa-link" aria-hidden="true"></i></a>Spark3&#x548C;hadoop&#x517C;&#x5BB9;&#x95EE;&#x9898;</h3>
<p>Spark 3.0 &#x5B98;&#x65B9;&#x9ED8;&#x8BA4;&#x652F;&#x6301;&#x7684;Hadoop&#x6700;&#x4F4E;&#x7248;&#x672C;&#x4E3A;2.7, Hive&#x6700;&#x4F4E;&#x7248;&#x672C;&#x4E3A; 1.2&#x3002;&#x6211;&#x4EEC;&#x5E73;&#x53F0;&#x4F7F;&#x7528;&#x7684;CDH 5.13,&#x5BF9;&#x5E94;&#x7684;&#x7248;&#x672C;&#x5206;&#x522B;&#x4E3A;hadoop-2.6.0, hive-1.1.0&#x3002;
&#x6240;&#x4EE5;&#x5728;&#x7F16;&#x8BD1;yarn&#x6A21;&#x5757;&#x4F1A;&#x62A5;&#x9519;&#xFF1A;
&#x5177;&#x4F53;&#x662F;/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala&#x7684;
298&#x884C;logAggregationContext.setRolledLogsIncludePattern(includePattern)
300&#x884C;logAggregationContext.setRolledLogsExcludePattern(excludePattern)&#x95EE;&#x9898;</p>
<p>&#x7531;&#x4E8E;&#x8FD9;&#x4E24;&#x4E2A;&#x65B9;&#x6CD5;&#x662F;hadoop2.6.4&#x6DFB;&#x52A0;&#x7684;&#xFF0C;&#x5982;&#x679C;&#x4F60;&#x7684;hadoop&#x7248;&#x672C;&#x4F4E;&#x4E8E;2.6.4&#xFF0C;&#x90A3;&#x4E48;&#x7F16;&#x8BD1;&#x5C31;&#x4F1A;&#x62A5;&#x9519;&#x3002;</p>
<p>&#x89E3;&#x51B3;&#x65B9;&#x6CD5;&#xFF1A;&#x53C2;&#x8003; <a href="https://github.com/apache/spark/pull/16884/files" target="_blank">https://github.com/apache/spark/pull/16884/files</a></p>
<h3 id="spark-30-&#x6574;&#x5408;hive&#x5F02;&#x5E38;&#x9AD8;&#x7248;&#x672C;hive&#x5FFD;&#x7565;"><a name="spark-30-&#x6574;&#x5408;hive&#x5F02;&#x5E38;&#x9AD8;&#x7248;&#x672C;hive&#x5FFD;&#x7565;" class="anchor-navigation-ex-anchor" href="#spark-30-&#x6574;&#x5408;hive&#x5F02;&#x5E38;&#x9AD8;&#x7248;&#x672C;hive&#x5FFD;&#x7565;"><i class="fa fa-link" aria-hidden="true"></i></a>Spark 3.0 &#x6574;&#x5408;hive&#x5F02;&#x5E38;(&#x9AD8;&#x7248;&#x672C;hive&#x5FFD;&#x7565;)</h3>
<p>&#x9519;&#x8BEF;&#x4FE1;&#x606F;&#x5927;&#x6982;&#x662F;&#x8FD9;&#x6837;&#xFF1A;</p>
<pre><code>hive.ql.metadata.HiveException: Unable to fetch table Invalid method name: get_table_req
</code></pre><p>&#x539F;&#x56E0;&#x662F;spark3&#x6E90;&#x7801;&#x9ED8;&#x8BA4;&#x4F7F;&#x7528;2.3.7&#x7248;&#x672C;&#x7684;hive&#xFF0C;&#x91CC;&#x9762;&#x7684;getTable&#x65B9;&#x6CD5;&#x8C03;&#x7528;&#x4E86;get_table_req,&#x800C;hive&#x5BA2;&#x6237;&#x7AEF;&#x7684;&#x7248;&#x672C;&lt;=1.2.x&#x627E;&#x4E0D;&#x5230;get_table_req&#x7684;&#x65B9;&#x6CD5;&#xFF0C;
&#x6240;&#x4EE5;&#x62A5;&#x4E86;Invalid method name:get_table_req</p>
<p>&#x89E3;&#x51B3;&#x65B9;&#x6CD5;&#xFF1A;&#x81EA;&#x5DF1;&#x624B;&#x52A8;&#x7F16;&#x8BD1;Spark&#xFF0C;&#x6307;&#x5B9A;hive&#x7684;&#x7248;&#x672C;&#x4E3A;1.2.1&#xFF0C;&#x6253;&#x5305;&#x7F16;&#x8BD1;Spark&#x7684;&#x65F6;&#x5019;&#x6307;&#x5B9A;-Phive-1.2</p>
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